Research Interests

My work is mainly concerned with the neural mechanisms that make decisions, and the relation of this to response time; it focuses particularly ion saccades, since where to look next is the single most frequent decision that we make (about 2-3 every second of our waking lives). But I am also interested in quantitative modelling generally in physiology, for instance of cardiac regulation, and have a passionate and continuing commitment to teaching, particularly in encouraging medical students to engage with fundamental concepts rather than rote-learning.

It is increasingly accepted that the brain makes decisions by accumulating information, a quasi-Bayesian process in which a neural signal representing likelihood rises steadily on presentation of a stimulus until it reaches a threshold criterion level at which a response is justified. My LATER model is probably the simplest such model, with very few parameters, and is capable of modelling data about the stochastic distribution of reaction times (which vary randomly from trial to trial) with remarkable accuracy: not just in simple tasks, but in more complex ones such as countermanding, anti-saccades and Wheeless trials, where it predicts the incidence of errors as well. As a result it is being increasingly employed all over the world as a way of obtaining accurate and quantitative measures of higher neural function, for instance in neurodegenerative disorders: with miniaturized portable equipment (a saccadometer) measurements can be made rapidly and non-invasively, and provide independent information about the two hemispheres.

One particular application that is likely to become very significant in the near future is in relation to the diagnosis and monitoring of traumatic brain injury (‘concussion’), a matter of increasing concern especially in young sportsmen and women, and also in military personnel.